code: def split_train_v_test(
      dir="/tmp",
      party1="alice",
      party2="bob",
      reduced=None,
      binary=False,
  ):
      """Gives Party 1 training data and Party 2 the test data"""
      mnist_norm, mnist_labels = _get_norm_mnist(dir, reduced, binary)
      mnist_train_norm, mnist_test_norm = mnist_norm
      mnist_train_labels, mnist_test_labels = mnist_labels
  
      torch.save(
          mnist_train_norm, os.path.join(dir, party1 + "_train.pth")
      )
      torch.save(
          mnist_test_norm, os.path.join(dir, party2 + "_test.pth")
      )
      torch.save(
          mnist_train_labels,
          os.path.join(dir, party1 + "_train_labels.pth"),
      )
      torch.save(
          mnist_test_labels,
          os.path.join(dir, party2 + "_test_labels.pth"),
      )
  
file_path: CrypTen/tutorials/mnist_utils.py
imports: import argparse
  import os
  import torch
  from torchvision import datasets, transforms
label_desc: Use image node_id 5 for calling a global function with example usage: split_train_v_test(dir, party1, party2, reduced, binary) without return types